A debugging method for maglev train suspension system based on digital twin technology

Abstract

The invention relates to a method for debugging a maglev train suspension system based on digital twin technology, comprising the following steps: a digital twin construction step: constructing a digital twin of the maglev train suspension system, and communicating between the digital twin and the maglev train suspension system Connection; levitation data collection and perception step: the levitation system of the maglev train collects and perceives levitation data through sensors, and transmits the levitation data to the digital twin in real time; levitation system debugging step: real-time observation and Debugging the suspension state of the digital twin body, thereby reacting to the suspension system of the maglev train. Compared with the prior art, the present invention effectively verifies the effectiveness of parameter debugging when the operating condition of the train changes significantly, further improves the debugging accuracy based on the digital twin virtual model, and improves the working environment of the debugging personnel, reducing the Human time cost and economic cost are reduced.

Description

technical field [0001] The invention relates to the field of rail transportation, in particular to a debugging method for a maglev train suspension system based on a digital twin technology. Background technique [0002] At present, the running speed of high-speed wheel-rail trains has reached 350km / h, and increasing the speed again will lead to increased wheel and rail wear, which in turn will lead to a doubled increase in operating costs. The maglev train ensures contactless operation between the rails during operation, and can achieve higher speed at a lower cost, thereby realizing short-time commuting between long-distance cities. In addition, because the wheel-rail contact is avoided, the mechanical noise during operation is effectively reduced, which is another reason why the existing wheel-rail trains cannot be compared. [0003] The stable suspension of the maglev train is one of the most important prerequisites to ensure its normal operation, and the debugging of t...

AI Technical Summary

Problems solved by technology

At present, the debugging of the suspension system needs to carry out on-site car-following tests, and the actual data can be observed through two-dimensional curves through CAN signals, but this debugging method requires a lot of manpower, time and economic costs

In addition, the suspension train has multiple car formations, and each car has multiple suspension points. Repeated observations of the two-dimensional curves of multiple suspension single points cannot be visualized, which may lead to poor debugging results and prolong debugging. time

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